A novel algorithm for ocean wave direction inversion from X-band radar images based on optical flow method

Wang, Li; Cheng, Yunfei; Hong, Lijuan; Liu, Xinyu

doi:10.1007/s13131-018-1201-9

Cited by 3 publications

(2 citation statements)

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“…The direction of flow fields is superposed by vertical and horizontal vectors indicating North and East. The actual flow direction is computed by composing the directions of point data, using Equation (2).…”

Section: Autocorrelation Analysis Of Directionmentioning

confidence: 99%

“…With recent advancements in data acquisition technology, the range and resolution of ocean flow field data being collected have both increased significantly, leading to a large amount of data with dense vector points [1,2]. Displaying all of the information contained in dense vector points on a large scale is not only tedious and difficult, but also leads to visualizations that are congested with an overabundance of map symbols.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Scale Representation of Ocean Flow Fields Based on Feature Analysis

Sun

Liu

et al. 2020

IJGI

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When it comes to feature retention in multi-scale representations of ocean flow fields, not all data points are equal. Therefore, this paper proposes a method of selecting data points based on their importance. First, an autocorrelation analysis is performed on flow speed and the rate of change in flow direction. Then, the magnitude of speed and variation in the rate of change in flow direction are classified. Feature regions are determined according to autocorrelation aggregation and classification analysis. Then, rough set theory and evidence theory are applied, using these results to determine the weights of different points. Finally, these weights are used to construct multi-scale representations of ocean flow fields, which effectively retain flow-field characteristics.

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Section: Autocorrelation Analysis Of Directionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%